Bone Ultrasound Segmentation Network Based on Sequential Attention and Local Phase Guidance

In the ultrasound assisted navigation of orthopaedics, the bone structure needs to be segmented accurately from the collected ultrasound images and displayed to the doctor to assist the intraoperative decision-making. However, it is difficult to segment bone structures from ultrasound images because of imaging noises, shadow artifacts and blurred bone boundaries. For solving this problem, this paper proposes a bone ultrasound image segmentation network based on sequential attention and local phase guidance. On the one hand, the network adaptively uses the relationship between frames of ultrasound sequence, that is, sequence attention, to assist the semantic segmentation of bone structures. On the other hand, the local phase guidance module is introduced to highlight the bone edge information and further improve the segmentation accuracy. We performed the cross validation, ablation experiments and the comparison experiments with the state-of-arts by using a dataset that contained 19 050 bone ultrasound images. The experimental results show that the proposed method has high accuracy and is superior to the existing bone segmentation methods. © 2024 Science Press. All rights reserved.